{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "vTOX0d3cmLQf"
   },
   "source": [
    "# EECS 498-007/598-005 Assignment 2-1: Linear Classifiers\n",
    "\n",
    "Before we start, please put your name and UMID in following format\n",
    "\n",
    ": Firstname LASTNAME, #00000000   //   e.g.) Justin JOHNSON, #12345678"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "tt7vq1h6mRto"
   },
   "source": [
    "**Your Answer:**   \n",
    "Your NAME, #XXXXXXXX"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "FrfeHl_-m4V-"
   },
   "source": [
    "## Setup Code\n",
    "Before getting started, we need to run some boilerplate code to set up our environment, same as Assignment 1. You'll need to rerun this setup code each time you start the notebook.\n",
    "\n",
    "First, run this cell load the autoreload extension. This allows us to edit .py source files, and re-import them into the notebook for a seamless editing and debugging experience."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1027,
     "status": "ok",
     "timestamp": 1600042524722,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "VyQblYp0nEZq",
    "outputId": "1902f06e-d588-4ac5-97e9-299a8b2314f8"
   },
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Q7ymI0aZ2W1b"
   },
   "source": [
    "### Google Colab Setup\n",
    "Next we need to run a few commands to set up our environment on Google Colab. If you are running this notebook on a local machine you can skip this section.\n",
    "\n",
    "Run the following cell to mount your Google Drive. Follow the link, sign in to your Google account (the same account you used to store this notebook!) and copy the authorization code into the text box that appears below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 344,
     "status": "ok",
     "timestamp": 1600042525194,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "c_LLpLyC2eau",
    "outputId": "5cc38a97-5396-4afc-ba83-400f486d22fd"
   },
   "outputs": [],
   "source": [
    "from google.colab import drive\n",
    "drive.mount('/content/drive')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "mbq-UT8J2mnv"
   },
   "source": [
    "Now recall the path in your Google Drive where you uploaded this notebook, fill it in below. If everything is working correctly then running the folowing cell should print the filenames from the assignment:\n",
    "\n",
    "```\n",
    "['two_layer_net.ipynb', 'eecs598', 'two_layer_net.py', 'linear_classifier.py', 'linear_classifier.ipynb', 'a2_helpers.py']\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 303,
     "status": "ok",
     "timestamp": 1600042532597,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "WcrhTOZW243H",
    "outputId": "f294fd3e-3860-456f-b2f7-05bf799e60e2"
   },
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "# TODO: Fill in the Google Drive path where you uploaded the assignment\n",
    "# Example: If you create a 2020FA folder and put all the files under A2 folder, then '2020FA/A2'\n",
    "# GOOGLE_DRIVE_PATH_AFTER_MYDRIVE = '2020FA/A2'\n",
    "GOOGLE_DRIVE_PATH_AFTER_MYDRIVE = None\n",
    "GOOGLE_DRIVE_PATH = os.path.join('drive', 'My Drive', GOOGLE_DRIVE_PATH_AFTER_MYDRIVE)\n",
    "print(os.listdir(GOOGLE_DRIVE_PATH))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "xegb0uDA232J"
   },
   "source": [
    "Once you have successfully mounted your Google Drive and located the path to this assignment, run th following cell to allow us to import from the `.py` files of this assignment. If it works correctly, it should print the message:\n",
    "\n",
    "```\n",
    "Hello from linear_classifier.py!\n",
    "```\n",
    "\n",
    "as well as the last edit time for the file `linear_classifier.py`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 787,
     "status": "ok",
     "timestamp": 1600042538544,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "AhGQF5sw3Fas",
    "outputId": "5e77649b-b04d-47a8-f67a-837516eb5874"
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append(GOOGLE_DRIVE_PATH)\n",
    "\n",
    "import time, os\n",
    "os.environ[\"TZ\"] = \"US/Eastern\"\n",
    "time.tzset()\n",
    "\n",
    "from linear_classifier import hello_linear_classifier\n",
    "hello_linear_classifier()\n",
    "\n",
    "linear_classifier_path = os.path.join(GOOGLE_DRIVE_PATH, 'linear_classifier.py')\n",
    "linear_classifier_edit_time = time.ctime(os.path.getmtime(linear_classifier_path))\n",
    "print('linear_classifier.py last edited on %s' % linear_classifier_edit_time)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "ynKS05gJ4iBo"
   },
   "source": [
    "# Data preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "fN1SShPR4lJV"
   },
   "source": [
    "## Setup code\n",
    "Run some setup code for this notebook: Import some useful packages and increase the default figure size."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 255,
     "status": "ok",
     "timestamp": 1600042538923,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "VUCKw4Tl1ddj"
   },
   "outputs": [],
   "source": [
    "import eecs598\n",
    "import torch\n",
    "import torchvision\n",
    "import matplotlib.pyplot as plt\n",
    "import statistics\n",
    "import random\n",
    "import time\n",
    "import math\n",
    "%matplotlib inline\n",
    "\n",
    "\n",
    "plt.rcParams['figure.figsize'] = (10.0, 8.0)\n",
    "plt.rcParams['font.size'] = 16"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "lhqpd2IN2O-K"
   },
   "source": [
    "Starting in this assignment, we will use the GPU to accelerate our computation. Run this cell to make sure you are using a GPU."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 436,
     "status": "ok",
     "timestamp": 1600042539504,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "SGDxdBIMRX6b",
    "outputId": "2fa0477a-31b2-4612-a154-b297589bd9e4"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Good to go!\n"
     ]
    }
   ],
   "source": [
    "if torch.cuda.is_available:\n",
    "  print('Good to go!')\n",
    "else:\n",
    "  print('Please set GPU via Edit -> Notebook Settings.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "-Yv3zQYw5B3s"
   },
   "source": [
    "## Load the CIFAR-10 dataset\n",
    "Then, we will first load the CIFAR-10 dataset, same as knn. The utility function `eecs598.data.preprocess_cifar10()` returns the entire CIFAR-10 dataset as a set of six **Torch tensors**:\n",
    "\n",
    "- `X_train` contains all training images (real numbers in the range $[0, 1]$)\n",
    "- `y_train` contains all training labels (integers in the range $[0, 9]$)\n",
    "- `X_val` contains all validation images\n",
    "- `y_val` contains all validation labels\n",
    "- `X_test` contains all test images\n",
    "- `y_test` contains all test labels\n",
    "\n",
    "In this notebook we will use the **bias trick**: By adding an extra constant feature of ones to each image, we avoid the need to keep track of a bias vector; the bias will be encoded as the part of the weight matrix that interacts with the constant ones in the input.\n",
    "\n",
    "In the `two_layer_net.ipynb` notebook that follows this one, we will not use the bias trick.\n",
    "\n",
    "We can learn more about the `eecs598.data.preprocess_cifar10` function by invoking the `help` command:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 595
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 445,
     "status": "ok",
     "timestamp": 1600042539876,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "V2mFlFmQ1ddm",
    "outputId": "38262fbd-4b9c-45d2-f38a-83136aa24492"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function preprocess_cifar10 in module eecs598.data:\n",
      "\n",
      "preprocess_cifar10(cuda=True, show_examples=True, bias_trick=False, validation_ratio=0.2, dtype=torch.float32)\n",
      "    Returns a preprocessed version of the CIFAR10 dataset, automatically\n",
      "    downloading if necessary. We perform the following steps:\n",
      "    \n",
      "    (0) [Optional] Visualize some images from the dataset\n",
      "    (1) Normalize the data by subtracting the mean\n",
      "    (2) Reshape each image of shape (3, 32, 32) into a vector of shape (3072,)\n",
      "    (3) [Optional] Bias trick: add an extra dimension of ones to the data\n",
      "    (4) Carve out a validation set from the training set\n",
      "    \n",
      "    Inputs:\n",
      "    - cuda: If true, move the entire dataset to the GPU\n",
      "    - validation_ratio: Float in the range (0, 1) giving the fraction of the train\n",
      "      set to reserve for validation\n",
      "    - bias_trick: Boolean telling whether or not to apply the bias trick\n",
      "    - show_examples: Boolean telling whether or not to visualize data samples\n",
      "    - dtype: Optional, data type of the input image X\n",
      "    \n",
      "    Returns a dictionary with the following keys:\n",
      "    - 'X_train': `dtype` tensor of shape (N_train, D) giving training images\n",
      "    - 'X_val': `dtype` tensor of shape (N_val, D) giving val images\n",
      "    - 'X_test': `dtype` tensor of shape (N_test, D) giving test images\n",
      "    - 'y_train': int64 tensor of shape (N_train,) giving training labels\n",
      "    - 'y_val': int64 tensor of shape (N_val,) giving val labels\n",
      "    - 'y_test': int64 tensor of shape (N_test,) giving test labels\n",
      "    \n",
      "    N_train, N_val, and N_test are the number of examples in the train, val, and\n",
      "    test sets respectively. The precise values of N_train and N_val are determined\n",
      "    by the input parameter validation_ratio. D is the dimension of the image data;\n",
      "    if bias_trick is False, then D = 32 * 32 * 3 = 3072;\n",
      "    if bias_trick is True then D = 1 + 32 * 32 * 3 = 3073.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "help(eecs598.data.preprocess_cifar10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "COCx2kM6XB3K"
   },
   "source": [
    "We can now run the `eecs598.data.preprocess` function to get our data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 568
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 3040,
     "status": "ok",
     "timestamp": 1600042542853,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "r_BhZ_6_XB3K",
    "outputId": "92b4e51e-d0e0-43c7-e1f0-d3a116b1f06d"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train data shape:  torch.Size([40000, 3073])\n",
      "Train labels shape:  torch.Size([40000])\n",
      "Validation data shape:  torch.Size([10000, 3073])\n",
      "Validation labels shape:  torch.Size([10000])\n",
      "Test data shape:  torch.Size([10000, 3073])\n",
      "Test labels shape:  torch.Size([10000])\n"
     ]
    }
   ],
   "source": [
    "# Invoke the above function to get our data. \n",
    "import eecs598\n",
    "\n",
    "eecs598.reset_seed(0)\n",
    "data_dict = eecs598.data.preprocess_cifar10(bias_trick=True, cuda=True, dtype=torch.float64)\n",
    "print('Train data shape: ', data_dict['X_train'].shape)\n",
    "print('Train labels shape: ', data_dict['y_train'].shape)\n",
    "print('Validation data shape: ', data_dict['X_val'].shape)\n",
    "print('Validation labels shape: ', data_dict['y_val'].shape)\n",
    "print('Test data shape: ', data_dict['X_test'].shape)\n",
    "print('Test labels shape: ', data_dict['y_test'].shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "0Lvdm4fm7iJC"
   },
   "source": [
    "# SVM Classifier\n",
    "\n",
    "In this section, you will:\n",
    "    \n",
    "- implement a fully-vectorized **loss function** for the SVM\n",
    "- implement the fully-vectorized expression for its **analytic gradient**\n",
    "- **check your implementation** using numerical gradient\n",
    "- use a validation set to **tune the learning rate and regularization** strength\n",
    "- **optimize** the loss function with **SGD**\n",
    "- **visualize** the final learned weights\n",
    "\n",
    "In Assignment 2, you SHOULD NOT use \".to()\" or \".cuda()\" in each implementation block. Otherwise, your implementation would gives you an error in Autograder end."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "xTI4qN7S9aTr"
   },
   "source": [
    "First, we will test the naive version of svm loss in `linear_classifier.py`. Let's first try the naive implementation of the loss we provided for you. You will get 9.000197. (Note: we've provided the `loss` part of the `svm_loss_naive` function, so you don't need to re-implement in `svm_loss_naive`. However, if your loss value doesn't match, then please report this to [Piazza](https://piazza.com/class/ke3a8m6u5wx647))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 22697,
     "status": "ok",
     "timestamp": 1600042563158,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "Hxzu2uZq9P8P",
    "outputId": "6c68b037-6ed6-4fbd-8dbf-faab64a41396"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss: 9.000888\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "from linear_classifier import svm_loss_naive\n",
    "\n",
    "eecs598.reset_seed(0)\n",
    "# generate a random SVM weight tensor of small numbers\n",
    "W = torch.randn(3073, 10, dtype=data_dict['X_val'].dtype, device=data_dict['X_val'].device) * 0.0001 \n",
    "\n",
    "loss, _grad_ = svm_loss_naive(W, data_dict['X_val'], data_dict['y_val'], 0.000005)\n",
    "print('loss: %f' % (loss, ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "9LbRTXJ39Yp8"
   },
   "source": [
    "The `_grad_` returned from the function above is right now all zero. Derive and implement the gradient for the SVM cost function and implement it inline inside the function `svm_loss_naive`, by filing out the TODO blocks. You will find it helpful to interleave your new code inside the existing function.\n",
    "\n",
    "To check that you have implemented the gradient correctly, we will use **numeric gradient checking**: we will use a finite differences approach to numerically estimate the gradient of the forward pass, and compare this numeric gradient to the analytic gradient that you implemented.\n",
    "\n",
    "We have provided a function `eecs598.grad.grad_check_sparse` to help with numeric gradient checking. You can learn more about this function using the `help` command:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 323
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 22271,
     "status": "ok",
     "timestamp": 1600042563159,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "wzie6dahXB3Q",
    "outputId": "3d22fb55-f37d-476f-cf82-6fa2e077020e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function grad_check_sparse in module eecs598.grad:\n",
      "\n",
      "grad_check_sparse(f, x, analytic_grad, num_checks=10, h=1e-07)\n",
      "    Utility function to perform numeric gradient checking. We use the centered\n",
      "    difference formula to compute a numeric derivative:\n",
      "    \n",
      "    f'(x) =~ (f(x + h) - f(x - h)) / (2h)\n",
      "    \n",
      "    Rather than computing a full numeric gradient, we sparsely sample a few\n",
      "    dimensions along which to compute numeric derivatives.\n",
      "    \n",
      "    Inputs:\n",
      "    - f: A function that inputs a torch tensor and returns a torch scalar\n",
      "    - x: A torch tensor giving the point at which to evaluate the numeric gradient\n",
      "    - analytic_grad: A torch tensor giving the analytic gradient of f at x\n",
      "    - num_checks: The number of dimensions along which to check\n",
      "    - h: Step size for computing numeric derivatives\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "help(eecs598.grad.grad_check_sparse)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "pKc4v6a8XB3T"
   },
   "source": [
    "Now run the following to perform numeric gradient checking on the gradients of your SVM loss. You should see relative errors less than `1e-5`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 187
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 24726,
     "status": "ok",
     "timestamp": 1600042565991,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "o3sMha4i9p_V",
    "outputId": "728087f4-d83d-476c-d8b6-57e40378375e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numerical: 0.031599 analytic: 0.031599, relative error: 3.139148e-07\n",
      "numerical: 0.111444 analytic: 0.111444, relative error: 9.893848e-10\n",
      "numerical: 0.011204 analytic: 0.011204, relative error: 1.003052e-06\n",
      "numerical: -0.046128 analytic: -0.046128, relative error: 1.470228e-08\n",
      "numerical: 0.071948 analytic: 0.071948, relative error: 1.000117e-07\n",
      "numerical: 0.025688 analytic: 0.025688, relative error: 1.051337e-06\n",
      "numerical: 0.185388 analytic: 0.185388, relative error: 7.039118e-09\n",
      "numerical: -0.021740 analytic: -0.021740, relative error: 3.369463e-07\n",
      "numerical: -0.159613 analytic: -0.159613, relative error: 6.416943e-08\n",
      "numerical: 0.092690 analytic: 0.092690, relative error: 1.748534e-07\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "from linear_classifier import svm_loss_naive\n",
    "\n",
    "# Once you've implemented the gradient, recompute it with the code below\n",
    "# and gradient check it with the function we provided for you\n",
    "\n",
    "# Use a random W and a minibatch of data from the val set for gradient checking\n",
    "# For numeric gradient checking it is a good idea to use 64-bit floating point\n",
    "# numbers for increased numeric precision; however when actually training models\n",
    "# we usually use 32-bit floating point numbers for increased speed.\n",
    "eecs598.reset_seed(0)\n",
    "W = 0.0001 * torch.randn(3073, 10, dtype=data_dict['X_val'].dtype, device=data_dict['X_val'].device)\n",
    "batch_size = 64\n",
    "X_batch = data_dict['X_val'][:batch_size]\n",
    "y_batch = data_dict['y_val'][:batch_size]\n",
    "\n",
    "# Compute the loss and its gradient at W.\n",
    "# YOUR_TURN: implement the gradient part of 'svm_loss_naive' function in \"linear_classifier.py\"\n",
    "_, grad = svm_loss_naive(W, X_batch, y_batch, reg=0.0)\n",
    "\n",
    "# Numerically compute the gradient along several randomly chosen dimensions, and\n",
    "# compare them with your analytically computed gradient. The numbers should\n",
    "# match almost exactly along all dimensions.\n",
    "f = lambda w: svm_loss_naive(w, X_batch, y_batch, reg=0.0)[0]\n",
    "grad_numerical = eecs598.grad.grad_check_sparse(f, W, grad)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "lSdsG-L292Ww"
   },
   "source": [
    "Let's do the gradient check once again with regularization turned on. (You didn't forget the regularization gradient, did you?)\n",
    "\n",
    "You should see relative errors less than `1e-5`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 187
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 27345,
     "status": "ok",
     "timestamp": 1600042568998,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "bH6lXxVn9xZk",
    "outputId": "9de60bca-a304-42ef-9c71-896c7afd7e63"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numerical: 0.124849 analytic: 0.124849, relative error: 6.251581e-08\n",
      "numerical: 0.168915 analytic: 0.168915, relative error: 5.957873e-09\n",
      "numerical: 0.148752 analytic: 0.148752, relative error: 8.733009e-08\n",
      "numerical: -0.024936 analytic: -0.024936, relative error: 1.133872e-07\n",
      "numerical: -0.008570 analytic: -0.008570, relative error: 7.174549e-07\n",
      "numerical: -0.103155 analytic: -0.103155, relative error: 2.498757e-07\n",
      "numerical: -0.335573 analytic: -0.335573, relative error: 4.472387e-09\n",
      "numerical: -0.222176 analytic: -0.222176, relative error: 4.264915e-08\n",
      "numerical: 0.681163 analytic: 0.681163, relative error: 1.235571e-08\n",
      "numerical: -0.004090 analytic: -0.004089, relative error: 4.327973e-06\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "from linear_classifier import svm_loss_naive\n",
    "\n",
    "# Use a minibatch of data from the val set for gradient checking\n",
    "eecs598.reset_seed(0)\n",
    "W = 0.0001 * torch.randn(3073, 10, dtype=data_dict['X_val'].dtype, device=data_dict['X_val'].device)\n",
    "batch_size = 64\n",
    "X_batch = data_dict['X_val'][:batch_size]\n",
    "y_batch = data_dict['y_val'][:batch_size]\n",
    "\n",
    "# Compute the loss and its gradient at W.\n",
    "# YOUR_TURN: check your 'svm_loss_naive' implementation with different 'reg'\n",
    "_, grad = svm_loss_naive(W, X_batch, y_batch, reg=1e3) \n",
    "\n",
    "# Numerically compute the gradient along several randomly chosen dimensions, and\n",
    "# compare them with your analytically computed gradient. The numbers should\n",
    "# match almost exactly along all dimensions.\n",
    "f = lambda w: svm_loss_naive(w, X_batch, y_batch, reg=1e3)[0]\n",
    "grad_numerical = eecs598.grad.grad_check_sparse(f, W, grad)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "sc5Wtu-e-WlI"
   },
   "source": [
    "Now, let's implement vectorized version of SVM: `svm_loss_vectorized`. It should compute the same inputs and outputs as the naive version before, but it should involve **no explicit loops**.\n",
    "\n",
    "Let's first check the speed and performance bewteen the non-vectorized and the vectorized version. You should see a 15-120x speedup. PyTorch does some extra setup the first time you run CUDA code, so **you may need to run this cell more than once to see the desired speedup**.\n",
    "\n",
    "(Note: It may have some difference, but should be less than 1e-6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 85
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 27538,
     "status": "ok",
     "timestamp": 1600042569595,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "pBLqLTAGo1Rs",
    "outputId": "89bba281-36e9-4f15-8f30-a0100c48ca57"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Naive loss: 9.002394e+00 computed in 989.90ms\n",
      "Vectorized loss: 9.002394e+00 computed in 7.12ms\n",
      "Difference: 1.54e-09\n",
      "Speedup: 139.13X\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "from linear_classifier import svm_loss_naive, svm_loss_vectorized\n",
    "\n",
    "# Use random weights and a minibatch of val data for gradient checking\n",
    "eecs598.reset_seed(0)\n",
    "W = 0.0001 * torch.randn(3073, 10, dtype=data_dict['X_val'].dtype, device=data_dict['X_val'].device)\n",
    "X_batch = data_dict['X_val'][:128]\n",
    "y_batch = data_dict['y_val'][:128]\n",
    "reg = 0.000005\n",
    "\n",
    "# Run and time the naive version\n",
    "torch.cuda.synchronize()\n",
    "tic = time.time()\n",
    "loss_naive, grad_naive = svm_loss_naive(W, X_batch, y_batch, reg)\n",
    "torch.cuda.synchronize()\n",
    "toc = time.time()\n",
    "ms_naive = 1000.0 * (toc - tic)\n",
    "print('Naive loss: %e computed in %.2fms' % (loss_naive, ms_naive))\n",
    "\n",
    "# Run and time the vectorized version\n",
    "torch.cuda.synchronize()\n",
    "tic = time.time()\n",
    "# YOUR_TURN: implement the loss part of 'svm_loss_vectorized' function in \"linear_classifier.py\"\n",
    "loss_vec, _ = svm_loss_vectorized(W, X_batch, y_batch, reg)\n",
    "torch.cuda.synchronize()\n",
    "toc = time.time()\n",
    "ms_vec = 1000.0 * (toc - tic)\n",
    "print('Vectorized loss: %e computed in %.2fms' % (loss_vec, ms_vec))\n",
    "\n",
    "# The losses should match but your vectorized implementation should be much faster.\n",
    "print('Difference: %.2e' % (loss_naive - loss_vec))\n",
    "print('Speedup: %.2fX' % (ms_naive / ms_vec))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "cRDPpAMl-0WD"
   },
   "source": [
    "Then, let's compute the gradient of the loss function. We can check the difference of gradient as well. (The error should be less than 1e-6)\n",
    "\n",
    "Now implement a vectorized version of the gradient computation in `svm_loss_vectorize` above. Run the cell below to compare the gradient of your naive and vectorized implementations. The difference between the gradients should be less than `1e-6`, and the vectorized version should run 15-120x faster.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 85
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 27496,
     "status": "ok",
     "timestamp": 1600042569954,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "3_SyWrTJ-OfX",
    "outputId": "333f5263-a25c-405a-95ab-257ca10064bf"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Naive loss and gradient: computed in 322.71ms\n",
      "Vectorized loss and gradient: computed in 1.00ms\n",
      "Gradient difference: 1.82e-14\n",
      "Speedup: 322.73X\n"
     ]
    }
   ],
   "source": [
    "# The naive implementation and the vectorized implementation should match, but\n",
    "# the vectorized version should still be much faster.\n",
    "\n",
    "import eecs598\n",
    "from linear_classifier import svm_loss_naive, svm_loss_vectorized\n",
    "\n",
    "# Use random weights and a minibatch of val data for gradient checking\n",
    "eecs598.reset_seed(0)\n",
    "W = 0.0001 * torch.randn(3073, 10, dtype=data_dict['X_val'].dtype, device=data_dict['X_val'].device)\n",
    "X_batch = data_dict['X_val'][:128]\n",
    "y_batch = data_dict['y_val'][:128]\n",
    "reg = 0.000005\n",
    "\n",
    "# Run and time the naive version\n",
    "torch.cuda.synchronize()\n",
    "tic = time.time()\n",
    "_, grad_naive = svm_loss_naive(W, X_batch, y_batch, 0.000005)\n",
    "torch.cuda.synchronize()\n",
    "toc = time.time()\n",
    "ms_naive = 1000.0 * (toc - tic)\n",
    "print('Naive loss and gradient: computed in %.2fms' % ms_naive)\n",
    "\n",
    "# Run and time the vectorized version\n",
    "torch.cuda.synchronize()\n",
    "tic = time.time()\n",
    "# YOUR_TURN: implement the gradient part of 'svm_loss_vectorized' function in \"linear_classifier.py\"\n",
    "_, grad_vec = svm_loss_vectorized(W, X_batch, y_batch, 0.000005)\n",
    "torch.cuda.synchronize()\n",
    "toc = time.time()\n",
    "ms_vec = 1000.0 * (toc - tic)\n",
    "print('Vectorized loss and gradient: computed in %.2fms' % ms_vec)\n",
    "\n",
    "# The loss is a single number, so it is easy to compare the values computed\n",
    "# by the two implementations. The gradient on the other hand is a tensor, so\n",
    "# we use the Frobenius norm to compare them.\n",
    "grad_difference = torch.norm(grad_naive - grad_vec, p='fro')\n",
    "print('Gradient difference: %.2e' % grad_difference)\n",
    "print('Speedup: %.2fX' % (ms_naive / ms_vec))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "uU852IitCtrC"
   },
   "source": [
    "Now that we have an efficient vectorized implementation of the SVM loss and its gradient, we can implement a training pipeline for linear classifiers.\n",
    "\n",
    "Please complete the implementation of `train_linear_classifier` in `linear_classifer.py`.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "c6IL1_D9wCbF"
   },
   "source": [
    "Once you have implemented the training function, run the following cell to train a linear classifier using some default hyperparameters:\n",
    "\n",
    "(You should see a final loss close to 9.0, and your training loop should run in about two seconds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 289
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 29022,
     "status": "ok",
     "timestamp": 1600042572063,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "QaEZkCe3-kOu",
    "outputId": "d0bb5f29-d597-4185-855e-beba0c8c325c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 0 / 1500: loss 9.000016\n",
      "iteration 100 / 1500: loss 8.999993\n",
      "iteration 200 / 1500: loss 9.000009\n",
      "iteration 300 / 1500: loss 8.999997\n",
      "iteration 400 / 1500: loss 9.000010\n",
      "iteration 500 / 1500: loss 9.000003\n",
      "iteration 600 / 1500: loss 9.000004\n",
      "iteration 700 / 1500: loss 9.000002\n",
      "iteration 800 / 1500: loss 9.000005\n",
      "iteration 900 / 1500: loss 9.000005\n",
      "iteration 1000 / 1500: loss 9.000003\n",
      "iteration 1100 / 1500: loss 9.000022\n",
      "iteration 1200 / 1500: loss 9.000020\n",
      "iteration 1300 / 1500: loss 9.000003\n",
      "iteration 1400 / 1500: loss 9.000012\n",
      "That took 2.692416s\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "from linear_classifier import svm_loss_vectorized, train_linear_classifier\n",
    "\n",
    "# fix random seed before we perform this operation\n",
    "eecs598.reset_seed(0)\n",
    "\n",
    "torch.cuda.synchronize()\n",
    "tic = time.time()\n",
    "\n",
    "# YOUR_TURN: Implement how to construct the batch, \n",
    "#            and how to update the weight in 'train_linear_classifier'\n",
    "W, loss_hist = train_linear_classifier(svm_loss_vectorized, None, \n",
    "                                       data_dict['X_train'], \n",
    "                                       data_dict['y_train'], \n",
    "                                       learning_rate=3e-11, reg=2.5e4,\n",
    "                                       num_iters=1500, verbose=True)\n",
    "\n",
    "torch.cuda.synchronize()\n",
    "toc = time.time()\n",
    "print('That took %fs' % (toc - tic))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "n8mz9aXfDrsF"
   },
   "source": [
    "A useful debugging strategy is to plot the loss as a function of iteration number. In this case it seems our hyperparameters are not good, since the training loss is not decreasing very fast.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 522
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 29018,
     "status": "ok",
     "timestamp": 1600042572490,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "JJ8GjaZS_MLe",
    "outputId": "5afa699a-6667-4c6f-982b-0ad610e6708a"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(loss_hist, 'o')\n",
    "plt.xlabel('Iteration number')\n",
    "plt.ylabel('Loss value')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "DRdfknKsE6F2"
   },
   "source": [
    "Then, let's move on to the prediction stage. We can evaluate the performance our trained model on both the training and validation set. You should see validation accuracy less than 20%."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 28692,
     "status": "ok",
     "timestamp": 1600042572491,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "YfToPzce_OBH",
    "outputId": "be83e513-152e-4a60-e7f9-37e590ea6d3c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training accuracy: 9.24%\n",
      "Validation accuracy: 9.00%\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "from linear_classifier import predict_linear_classifier\n",
    "\n",
    "# fix random seed before we perform this operation\n",
    "eecs598.reset_seed(0)\n",
    "\n",
    "# evaluate the performance on both the training and validation set\n",
    "# YOUR_TURN: Implement how to make a prediction with the trained weight \n",
    "#            in 'predict_linear_classifier'\n",
    "y_train_pred = predict_linear_classifier(W, data_dict['X_train'])\n",
    "train_acc = 100.0 * (data_dict['y_train'] == y_train_pred).double().mean().item()\n",
    "print('Training accuracy: %.2f%%' % train_acc)\n",
    "\n",
    "y_val_pred = predict_linear_classifier(W, data_dict['X_val'])\n",
    "val_acc = 100.0 * (data_dict['y_val'] == y_val_pred).double().mean().item()\n",
    "print('Validation accuracy: %.2f%%' % val_acc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "VWIyGnMOFOV8"
   },
   "source": [
    "Unfortunately, the performance of our initial model is quite bad. To find a better hyperparamters, we first modulized the functions that we've implemented as LinearSVM."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "taNmjt2wGJQr"
   },
   "source": [
    "Now, please use the validation set to tune hyperparameters (regularization strength and learning rate). You should experiment with different ranges for the learning rates and regularization strengths.\n",
    "\n",
    "To get full credit for the assignment your best model found through cross-validation should achieve an accuracy of at least 37% on the validation set.\n",
    "\n",
    "(Our best model got over 38.1% -- did you beat us?)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 595
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 76733,
     "status": "ok",
     "timestamp": 1600042621103,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "oVMsJ9Ti_Ude",
    "outputId": "2f48ea8d-b1da-4e84-ad60-6ba99cd564a7"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training SVM 1 / 24 with learning_rate=1.000000e-04 and reg=1.000000e+00\n",
      "Training SVM 2 / 24 with learning_rate=1.000000e-04 and reg=1.000000e+01\n",
      "Training SVM 3 / 24 with learning_rate=1.000000e-04 and reg=3.000000e+00\n",
      "Training SVM 4 / 24 with learning_rate=1.000000e-04 and reg=5.000000e+00\n",
      "Training SVM 5 / 24 with learning_rate=3.000000e-03 and reg=1.000000e+00\n",
      "Training SVM 6 / 24 with learning_rate=3.000000e-03 and reg=1.000000e+01\n",
      "Training SVM 7 / 24 with learning_rate=3.000000e-03 and reg=3.000000e+00\n",
      "Training SVM 8 / 24 with learning_rate=3.000000e-03 and reg=5.000000e+00\n",
      "Training SVM 9 / 24 with learning_rate=1.000000e-03 and reg=1.000000e+00\n",
      "Training SVM 10 / 24 with learning_rate=1.000000e-03 and reg=1.000000e+01\n",
      "Training SVM 11 / 24 with learning_rate=1.000000e-03 and reg=3.000000e+00\n",
      "Training SVM 12 / 24 with learning_rate=1.000000e-03 and reg=5.000000e+00\n",
      "Training SVM 13 / 24 with learning_rate=1.000000e-02 and reg=1.000000e+00\n",
      "Training SVM 14 / 24 with learning_rate=1.000000e-02 and reg=1.000000e+01\n",
      "Training SVM 15 / 24 with learning_rate=1.000000e-02 and reg=3.000000e+00\n",
      "Training SVM 16 / 24 with learning_rate=1.000000e-02 and reg=5.000000e+00\n",
      "Training SVM 17 / 24 with learning_rate=3.000000e-02 and reg=1.000000e+00\n",
      "Training SVM 18 / 24 with learning_rate=3.000000e-02 and reg=1.000000e+01\n",
      "Training SVM 19 / 24 with learning_rate=3.000000e-02 and reg=3.000000e+00\n",
      "Training SVM 20 / 24 with learning_rate=3.000000e-02 and reg=5.000000e+00\n",
      "Training SVM 21 / 24 with learning_rate=1.000000e-01 and reg=1.000000e+00\n",
      "Training SVM 22 / 24 with learning_rate=1.000000e-01 and reg=1.000000e+01\n",
      "Training SVM 23 / 24 with learning_rate=1.000000e-01 and reg=3.000000e+00\n",
      "Training SVM 24 / 24 with learning_rate=1.000000e-01 and reg=5.000000e+00\n",
      "lr 1.000000e-04 reg 1.000000e+00 train accuracy: 33.290000 val accuracy: 32.450000\n",
      "lr 1.000000e-04 reg 3.000000e+00 train accuracy: 32.180000 val accuracy: 31.840000\n",
      "lr 1.000000e-04 reg 5.000000e+00 train accuracy: 31.045000 val accuracy: 30.890000\n",
      "lr 1.000000e-04 reg 1.000000e+01 train accuracy: 29.290000 val accuracy: 29.220000\n",
      "lr 1.000000e-03 reg 1.000000e+00 train accuracy: 36.050000 val accuracy: 35.210000\n",
      "lr 1.000000e-03 reg 3.000000e+00 train accuracy: 32.957500 val accuracy: 32.850000\n",
      "lr 1.000000e-03 reg 5.000000e+00 train accuracy: 31.190000 val accuracy: 31.540000\n",
      "lr 1.000000e-03 reg 1.000000e+01 train accuracy: 29.067500 val accuracy: 28.770000\n",
      "lr 3.000000e-03 reg 1.000000e+00 train accuracy: 35.772500 val accuracy: 35.050000\n",
      "lr 3.000000e-03 reg 3.000000e+00 train accuracy: 32.770000 val accuracy: 32.800000\n",
      "lr 3.000000e-03 reg 5.000000e+00 train accuracy: 31.272500 val accuracy: 31.380000\n",
      "lr 3.000000e-03 reg 1.000000e+01 train accuracy: 28.980000 val accuracy: 28.900000\n",
      "lr 1.000000e-02 reg 1.000000e+00 train accuracy: 34.682500 val accuracy: 34.270000\n",
      "lr 1.000000e-02 reg 3.000000e+00 train accuracy: 32.300000 val accuracy: 32.180000\n",
      "lr 1.000000e-02 reg 5.000000e+00 train accuracy: 30.927500 val accuracy: 30.710000\n",
      "lr 1.000000e-02 reg 1.000000e+01 train accuracy: 29.062500 val accuracy: 28.780000\n",
      "lr 3.000000e-02 reg 1.000000e+00 train accuracy: 31.542500 val accuracy: 31.300000\n",
      "lr 3.000000e-02 reg 3.000000e+00 train accuracy: 27.755000 val accuracy: 27.660000\n",
      "lr 3.000000e-02 reg 5.000000e+00 train accuracy: 25.022500 val accuracy: 24.980000\n",
      "lr 3.000000e-02 reg 1.000000e+01 train accuracy: 19.927500 val accuracy: 19.950000\n",
      "lr 1.000000e-01 reg 1.000000e+00 train accuracy: 20.385000 val accuracy: 19.870000\n",
      "lr 1.000000e-01 reg 3.000000e+00 train accuracy: 18.342500 val accuracy: 17.980000\n",
      "lr 1.000000e-01 reg 5.000000e+00 train accuracy: 19.197500 val accuracy: 19.180000\n",
      "lr 1.000000e-01 reg 1.000000e+01 train accuracy: 6.072500 val accuracy: 5.860000\n",
      "best validation accuracy achieved during cross-validation: 35.210000\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import eecs598\n",
    "from linear_classifier import LinearSVM, svm_get_search_params, test_one_param_set\n",
    "\n",
    "# YOUR_TURN: find the best learning_rates and regularization_strengths combination\n",
    "#            in 'svm_get_search_params'\n",
    "learning_rates, regularization_strengths = svm_get_search_params()\n",
    "num_models = len(learning_rates) * len(regularization_strengths)\n",
    "\n",
    "####\n",
    "# It is okay to comment out the following conditions when you are working on svm_get_search_params.\n",
    "# But, please do not forget to reset back to the original setting once you are done.\n",
    "if num_models > 25:\n",
    "  raise Exception(\"Please do not test/submit more than 25 items at once\")\n",
    "elif num_models < 5:\n",
    "  raise Exception(\"Please present at least 5 parameter sets in your final ipynb\")\n",
    "####\n",
    "\n",
    "\n",
    "i = 0\n",
    "# results is dictionary mapping tuples of the form\n",
    "# (learning_rate, regularization_strength) to tuples of the form\n",
    "# (train_acc, val_acc). \n",
    "results = {}\n",
    "best_val = -1.0   # The highest validation accuracy that we have seen so far.\n",
    "best_svm_model = None # The LinearSVM object that achieved the highest validation rate.\n",
    "num_iters = 2000 # number of iterations\n",
    "\n",
    "for lr in learning_rates:\n",
    "  for reg in regularization_strengths:\n",
    "    i += 1\n",
    "    print('Training SVM %d / %d with learning_rate=%e and reg=%e'\n",
    "          % (i, num_models, lr, reg))\n",
    "    \n",
    "    eecs598.reset_seed(0)\n",
    "    # YOUR_TURN: implement a function that gives the trained model with \n",
    "    #            train/validation accuracies in 'test_one_param_set'\n",
    "    #            (note: this function will be used in Softmax Classifier section as well)\n",
    "    cand_svm_model, cand_train_acc, cand_val_acc = test_one_param_set(LinearSVM(), data_dict, lr, reg, num_iters)\n",
    "\n",
    "    if cand_val_acc > best_val:\n",
    "      best_val = cand_val_acc\n",
    "      best_svm_model = cand_svm_model # save the svm\n",
    "    results[(lr, reg)] = (cand_train_acc, cand_val_acc)\n",
    "\n",
    "\n",
    "# Print out results.\n",
    "for lr, reg in sorted(results):\n",
    "  train_acc, val_acc = results[(lr, reg)]\n",
    "  print('lr %e reg %e train accuracy: %f val accuracy: %f' % (\n",
    "         lr, reg, train_acc, val_acc))\n",
    "    \n",
    "print('best validation accuracy achieved during cross-validation: %f' % best_val)\n",
    "\n",
    "# save the best model\n",
    "# path = os.path.join(GOOGLE_DRIVE_PATH, 'svm_best_model.pt')\n",
    "# best_svm_model.save(path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "wBbvJvMeGZ-7"
   },
   "source": [
    "Visualize the cross-validation results. You can use this as a debugging tool -- after examining the cross-validation results here, you may want to go back and rerun your cross-validation from above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 713
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 76677,
     "status": "ok",
     "timestamp": 1600042621429,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "QbPffK9H_ZGj",
    "outputId": "fc56518b-406e-40fc-db07-667ceb817fe5"
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 576x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_scatter = [math.log10(x[0]) for x in results]\n",
    "y_scatter = [math.log10(x[1]) for x in results]\n",
    "\n",
    "# plot training accuracy\n",
    "marker_size = 100\n",
    "colors = [results[x][0] for x in results]\n",
    "plt.scatter(x_scatter, y_scatter, marker_size, c=colors, cmap='viridis')\n",
    "plt.colorbar()\n",
    "plt.xlabel('log learning rate')\n",
    "plt.ylabel('log regularization strength')\n",
    "plt.title('CIFAR-10 training accuracy')\n",
    "plt.gcf().set_size_inches(8, 5)\n",
    "plt.show()\n",
    "\n",
    "# plot validation accuracy\n",
    "colors = [results[x][1] for x in results] # default size of markers is 20\n",
    "plt.scatter(x_scatter, y_scatter, marker_size, c=colors, cmap='viridis')\n",
    "plt.colorbar()\n",
    "plt.xlabel('log learning rate')\n",
    "plt.ylabel('log regularization strength')\n",
    "plt.title('CIFAR-10 validation accuracy')\n",
    "plt.gcf().set_size_inches(8, 5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "MCMVzxquGf1O"
   },
   "source": [
    "Evaluate the best svm on test set. To get full credit for the assignment you should achieve a test-set accuracy above 35%.\n",
    "\n",
    "(Our best was over 39.1% -- did you beat us?)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 76352,
     "status": "ok",
     "timestamp": 1600042621429,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "maJ7use3_soL",
    "outputId": "79a25bc9-9576-4316-aa61-558d92398101"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "linear SVM on raw pixels final test set accuracy: 0.356800\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "\n",
    "eecs598.reset_seed(0)\n",
    "y_test_pred = best_svm_model.predict(data_dict['X_test'])\n",
    "test_accuracy = torch.mean((data_dict['y_test'] == y_test_pred).double())\n",
    "print('linear SVM on raw pixels final test set accuracy: %f' % test_accuracy)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "I-QVIG4fGiqJ"
   },
   "source": [
    "Visualize the learned weights for each class. Depending on your choice of learning rate and regularization strength, these may or may not be nice to look at."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 385
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 76264,
     "status": "ok",
     "timestamp": 1600042621773,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "McLHYtFd_vSI",
    "outputId": "cf6c2474-a208-4947-cf5a-da4d08e03841"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x576 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "w = best_svm_model.W[:-1,:] # strip out the bias\n",
    "w = w.reshape(3, 32, 32, 10)\n",
    "w = w.transpose(0, 2).transpose(1, 0)\n",
    "\n",
    "w_min, w_max = torch.min(w), torch.max(w)\n",
    "classes = ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "for i in range(10):\n",
    "  plt.subplot(2, 5, i + 1)\n",
    "\n",
    "  # Rescale the weights to be between 0 and 255\n",
    "  wimg = 255.0 * (w[:, :, :, i].squeeze() - w_min) / (w_max - w_min)\n",
    "  plt.imshow(wimg.type(torch.uint8).cpu())\n",
    "  plt.axis('off')\n",
    "  plt.title(classes[i])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "DkuwyMY27RxS"
   },
   "source": [
    "# Softmax Classifier\n",
    "\n",
    "Similar to the SVM, you will:\n",
    "\n",
    "- implement a fully-vectorized **loss function** for the Softmax classifier\n",
    "- implement the fully-vectorized expression for its **analytic gradient**\n",
    "- **check your implementation** with numerical gradient\n",
    "- use a validation set to **tune the learning rate and regularization** strength\n",
    "- **optimize** the loss function with **SGD**\n",
    "- **visualize** the final learned weights\n",
    "\n",
    "As noted in the SVM section, you SHOULD NOT use \".to()\" or \".cuda()\" in each implementation block."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "hLJMVGtvIgo3"
   },
   "source": [
    "First, let's start from implementing the naive softmax loss function with nested loops in `softmax_loss_naive` function."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "cER8fiSq7Ys-"
   },
   "source": [
    "As a sanity check to see whether we have implemented the loss correctly, run the softmax classifier with a small random weight matrix and no regularization. You should see loss near log(10) = 2.3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 75605,
     "status": "ok",
     "timestamp": 1600042622065,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "V9q77O7F7VI6",
    "outputId": "47e913ca-0938-4b7d-8bec-703b0de6afcd"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss: 2.302826\n",
      "sanity check: 2.302585\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "from linear_classifier import softmax_loss_naive\n",
    "\n",
    "eecs598.reset_seed(0)\n",
    "# Generate a random softmax weight tensor and use it to compute the loss.\n",
    "W = 0.0001 * torch.randn(3073, 10, dtype=data_dict['X_val'].dtype, device=data_dict['X_val'].device)\n",
    "\n",
    "X_batch = data_dict['X_val'][:128]\n",
    "y_batch = data_dict['y_val'][:128]\n",
    "\n",
    "# YOUR_TURN: Complete the implementation of softmax_loss_naive and implement \n",
    "# a (naive) version of the gradient that uses nested loops.\n",
    "loss, _ = softmax_loss_naive(W, X_batch, y_batch, reg=0.0)\n",
    "\n",
    "# As a rough sanity check, our loss should be something close to log(10.0).\n",
    "print('loss: %f' % loss)\n",
    "print('sanity check: %f' % (math.log(10.0)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "5QJzUHl5I0HH"
   },
   "source": [
    "Next, we use gradient checking to debug the analytic gradient of our naive softmax loss function. If you've implemented the gradient correctly, you should see relative errors less than `1e-5`.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 187
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 78386,
     "status": "ok",
     "timestamp": 1600042625176,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "Lj6YpN3q1hVG",
    "outputId": "c66c4e7b-ae4d-4533-8921-bfa98d8e7d5f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numerical: 0.003046 analytic: 0.003046, relative error: 6.468497e-07\n",
      "numerical: 0.006308 analytic: 0.006308, relative error: 1.234992e-07\n",
      "numerical: 0.005392 analytic: 0.005392, relative error: 4.593635e-07\n",
      "numerical: 0.002581 analytic: 0.002581, relative error: 3.442300e-08\n",
      "numerical: 0.007512 analytic: 0.007512, relative error: 8.122736e-07\n",
      "numerical: 0.006417 analytic: 0.006417, relative error: 2.286038e-08\n",
      "numerical: 0.011391 analytic: 0.011391, relative error: 1.960823e-07\n",
      "numerical: 0.001822 analytic: 0.001822, relative error: 2.932218e-06\n",
      "numerical: -0.014710 analytic: -0.014710, relative error: 8.967622e-08\n",
      "numerical: -0.005153 analytic: -0.005153, relative error: 4.012889e-07\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "from linear_classifier import softmax_loss_naive\n",
    "\n",
    "eecs598.reset_seed(0)\n",
    "W = 0.0001 * torch.randn(3073, 10, dtype=data_dict['X_val'].dtype, device=data_dict['X_val'].device)\n",
    "\n",
    "X_batch = data_dict['X_val'][:128]\n",
    "y_batch = data_dict['y_val'][:128]\n",
    "\n",
    "# YOUR_TURN: Complete the implementation of softmax_loss_naive and implement \n",
    "# a (naive) version of the gradient that uses nested loops.\n",
    "_, grad = softmax_loss_naive(W, X_batch, y_batch, reg=0.0)\n",
    "\n",
    "f = lambda w: softmax_loss_naive(w, X_batch, y_batch, reg=0.0)[0]\n",
    "eecs598.grad.grad_check_sparse(f, W, grad, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "cFcgeajBI-L3"
   },
   "source": [
    "Let's perform another gradient check with regularization enabled. Again you should see relative errors less than `1e-5`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 187
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 80765,
     "status": "ok",
     "timestamp": 1600042627921,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "Ik0i21sszZzg",
    "outputId": "d6752510-e1e8-46a6-845d-a8da92c468d3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numerical: 0.004914 analytic: 0.004914, relative error: 2.907815e-08\n",
      "numerical: 0.005887 analytic: 0.005887, relative error: 8.060044e-07\n",
      "numerical: 0.006309 analytic: 0.006309, relative error: 1.643123e-07\n",
      "numerical: 0.001580 analytic: 0.001580, relative error: 1.790195e-06\n",
      "numerical: 0.005839 analytic: 0.005839, relative error: 6.556458e-07\n",
      "numerical: 0.006800 analytic: 0.006800, relative error: 5.004632e-07\n",
      "numerical: 0.011465 analytic: 0.011465, relative error: 2.593154e-07\n",
      "numerical: 0.002314 analytic: 0.002314, relative error: 4.575594e-07\n",
      "numerical: -0.016813 analytic: -0.016813, relative error: 9.876027e-08\n",
      "numerical: -0.006673 analytic: -0.006673, relative error: 1.337888e-08\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "from linear_classifier import softmax_loss_naive\n",
    "\n",
    "eecs598.reset_seed(128)\n",
    "W = 0.0001 * torch.randn(3073, 10, dtype=data_dict['X_val'].dtype, device=data_dict['X_val'].device)\n",
    "reg = 10.0\n",
    "\n",
    "X_batch = data_dict['X_val'][:128]\n",
    "y_batch = data_dict['y_val'][:128]\n",
    "\n",
    "# YOUR_TURN: Complete the gradient compuation part of softmax_loss_naive \n",
    "_, grad = softmax_loss_naive(W, X_batch, y_batch, reg)\n",
    "\n",
    "f = lambda w: softmax_loss_naive(w, X_batch, y_batch, reg)[0]\n",
    "eecs598.grad.grad_check_sparse(f, W, grad, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "JQgRzrdRJAm7"
   },
   "source": [
    "Then, let's move on to the vectorized form: `softmax_loss_vectorized`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "88xZ0rbLJGKV"
   },
   "source": [
    "Now that we have a naive implementation of the softmax loss function and its gradient, implement a vectorized version in softmax_loss_vectorized. The two versions should compute the same results, but the vectorized version should be much faster.\n",
    "\n",
    "The differences between the naive and vectorized losses and gradients should both be less than `1e-6`, and your vectorized implementation should be at least 20x faster than the naive implementation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 102
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 80384,
     "status": "ok",
     "timestamp": 1600042628071,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "lGNAe-oP1dds",
    "outputId": "b2bf5857-f19f-43ec-f00e-583ee8509277"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "naive loss: 2.302841e+00 computed in 908.978939s\n",
      "vectorized loss: 2.302841e+00 computed in 2.001762s\n",
      "Loss difference: 0.00e+00\n",
      "Gradient difference: 6.94e-16\n",
      "Speedup: 454.09X\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "from linear_classifier import softmax_loss_naive, softmax_loss_vectorized\n",
    "\n",
    "eecs598.reset_seed(0)\n",
    "W = 0.0001 * torch.randn(3073, 10, dtype=data_dict['X_val'].dtype, device=data_dict['X_val'].device)\n",
    "reg = 0.05\n",
    "\n",
    "X_batch = data_dict['X_val'][:128]\n",
    "y_batch = data_dict['y_val'][:128]\n",
    "\n",
    "# Run and time the naive version\n",
    "torch.cuda.synchronize()\n",
    "tic = time.time()\n",
    "loss_naive, grad_naive = softmax_loss_naive(W, X_batch, y_batch, reg)\n",
    "torch.cuda.synchronize()\n",
    "toc = time.time()\n",
    "ms_naive = 1000.0 * (toc - tic)\n",
    "print('naive loss: %e computed in %fs' % (loss_naive, ms_naive))\n",
    "\n",
    "# Run and time the vectorized version\n",
    "# YOUR_TURN: Complete the implementation of softmax_loss_vectorized\n",
    "torch.cuda.synchronize()\n",
    "tic = time.time()\n",
    "loss_vec, grad_vec = softmax_loss_vectorized(W, X_batch, y_batch, reg)\n",
    "torch.cuda.synchronize()\n",
    "toc = time.time()\n",
    "ms_vec = 1000.0 * (toc - tic)\n",
    "print('vectorized loss: %e computed in %fs' % (loss_vec, ms_vec))\n",
    "\n",
    "# we use the Frobenius norm to compare the two versions of the gradient.\n",
    "loss_diff = (loss_naive - loss_vec).abs().item()\n",
    "grad_diff = torch.norm(grad_naive - grad_vec, p='fro')\n",
    "print('Loss difference: %.2e' % loss_diff)\n",
    "print('Gradient difference: %.2e' % grad_diff)\n",
    "print('Speedup: %.2fX' % (ms_naive / ms_vec))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "bqZScXKyq6WB"
   },
   "source": [
    "Let's check that your implementation of the softmax loss is numerically stable.\n",
    "\n",
    "If either of the following print `nan` then you should double-check the numeric stability of your implementations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 80385,
     "status": "ok",
     "timestamp": 1600042628472,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "bCyFPWxxq58R",
    "outputId": "a6ad7d89-c604-4b17-f669-c23567a4da79"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 0 / 1: loss 768250002.302585\n",
      "iteration 0 / 1: loss 768250002.302585\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "from linear_classifier import softmax_loss_naive, softmax_loss_vectorized\n",
    "eecs598.reset_seed(0)\n",
    "device = data_dict['X_train'].device\n",
    "dtype = data_dict['X_train'].dtype\n",
    "D = data_dict['X_train'].shape[1]\n",
    "C = 10\n",
    "\n",
    "# YOUR_TURN??: train_linear_classifier should be same as what you've implemented in the SVM section\n",
    "W_ones = torch.ones(D, C, device=device, dtype=dtype)\n",
    "W, loss_hist = train_linear_classifier(softmax_loss_naive, W_ones, \n",
    "                                       data_dict['X_train'], \n",
    "                                       data_dict['y_train'], \n",
    "                                       learning_rate=1e-8, reg=2.5e4,\n",
    "                                       num_iters=1, verbose=True)\n",
    "\n",
    "\n",
    "W_ones = torch.ones(D, C, device=device, dtype=dtype)\n",
    "W, loss_hist = train_linear_classifier(softmax_loss_vectorized, W_ones, \n",
    "                                       data_dict['X_train'], \n",
    "                                       data_dict['y_train'], \n",
    "                                       learning_rate=1e-8, reg=2.5e4,\n",
    "                                       num_iters=1, verbose=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "kR4JGKoek8FB"
   },
   "source": [
    "Now lets train a softmax classifier with some default hyperparameters:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 289
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 81950,
     "status": "ok",
     "timestamp": 1600042630391,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "Kqga1rvjk7b8",
    "outputId": "c5e0bace-afc3-476b-a57c-92a2540b3dae"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iteration 0 / 1500: loss 2.303356\n",
      "iteration 100 / 1500: loss 2.303353\n",
      "iteration 200 / 1500: loss 2.303354\n",
      "iteration 300 / 1500: loss 2.303352\n",
      "iteration 400 / 1500: loss 2.303352\n",
      "iteration 500 / 1500: loss 2.303351\n",
      "iteration 600 / 1500: loss 2.303350\n",
      "iteration 700 / 1500: loss 2.303349\n",
      "iteration 800 / 1500: loss 2.303349\n",
      "iteration 900 / 1500: loss 2.303348\n",
      "iteration 1000 / 1500: loss 2.303347\n",
      "iteration 1100 / 1500: loss 2.303348\n",
      "iteration 1200 / 1500: loss 2.303347\n",
      "iteration 1300 / 1500: loss 2.303345\n",
      "iteration 1400 / 1500: loss 2.303345\n",
      "That took 2.141709s\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "from linear_classifier import softmax_loss_vectorized\n",
    "\n",
    "eecs598.reset_seed(0)\n",
    "\n",
    "torch.cuda.synchronize()\n",
    "tic = time.time()\n",
    "\n",
    "# YOUR_TURN??: train_linear_classifier should be same as what you've implemented in the SVM section\n",
    "W, loss_hist = train_linear_classifier(softmax_loss_vectorized, None, \n",
    "                                       data_dict['X_train'], \n",
    "                                       data_dict['y_train'], \n",
    "                                       learning_rate=1e-10, reg=2.5e4,\n",
    "                                       num_iters=1500, verbose=True)\n",
    "\n",
    "torch.cuda.synchronize()\n",
    "toc = time.time()\n",
    "print('That took %fs' % (toc - tic))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "QKjxCGwkorCc"
   },
   "source": [
    "Plot the loss curve:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 522
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 82110,
     "status": "ok",
     "timestamp": 1600042630932,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "K29x-DWNoujL",
    "outputId": "5d583690-69f6-427d-8f3c-953196eaaad3"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(loss_hist, 'o')\n",
    "plt.xlabel('Iteration number')\n",
    "plt.ylabel('Loss value')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "7WvpBuJWSwfd"
   },
   "source": [
    "Let's compute the accuracy of current model. It should be less than 10%."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 80994,
     "status": "ok",
     "timestamp": 1600042630933,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "zb8kY2MjSvfH",
    "outputId": "20712234-bea7-4540-af2b-1d1d010c2caa"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training accuracy: 8.90%\n",
      "validation accuracy: 8.54%\n"
     ]
    }
   ],
   "source": [
    "import eecs598\n",
    "from linear_classifier import predict_linear_classifier\n",
    "\n",
    "eecs598.reset_seed(0)\n",
    "\n",
    "# evaluate the performance on both the training and validation set\n",
    "# YOUR_TURN??: predict_linear_classifier should be same as what you've implemented before, in the SVM section\n",
    "y_train_pred = predict_linear_classifier(W, data_dict['X_train'])\n",
    "train_acc = 100.0 * (data_dict['y_train'] == y_train_pred).double().mean().item()\n",
    "print('training accuracy: %.2f%%' % train_acc)\n",
    "y_val_pred = predict_linear_classifier(W, data_dict['X_val'])\n",
    "val_acc = 100.0 * (data_dict['y_val'] == y_val_pred).double().mean().item()\n",
    "print('validation accuracy: %.2f%%' % val_acc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "IuV0BZvzJirI"
   },
   "source": [
    "Now use the validation set to tune hyperparameters (regularization strength and learning rate). You should experiment with different ranges for the learning rates and regularization strengths.\n",
    "\n",
    "To get full credit for the assignment, your best model found through cross-validation should achieve an accuracy above 0.37 on the validation set.\n",
    "\n",
    "(Our best model was above 39.8% -- did you beat us?)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 357
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 103159,
     "status": "ok",
     "timestamp": 1600042654105,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "68lmNVj31ddu",
    "outputId": "aacd16df-6ddf-4c3d-b854-337b4c16db83"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Softmax 1 / 24 with learning_rate=1.000000e-04 and reg=1.000000e+00\n",
      "Training Softmax 2 / 24 with learning_rate=1.000000e-04 and reg=1.000000e+01\n",
      "Training Softmax 3 / 24 with learning_rate=1.000000e-04 and reg=3.000000e+00\n",
      "Training Softmax 4 / 24 with learning_rate=1.000000e-04 and reg=5.000000e+00\n",
      "Training Softmax 5 / 24 with learning_rate=3.000000e-03 and reg=1.000000e+00\n",
      "Training Softmax 6 / 24 with learning_rate=3.000000e-03 and reg=1.000000e+01\n",
      "Training Softmax 7 / 24 with learning_rate=3.000000e-03 and reg=3.000000e+00\n",
      "Training Softmax 8 / 24 with learning_rate=3.000000e-03 and reg=5.000000e+00\n",
      "Training Softmax 9 / 24 with learning_rate=1.000000e-03 and reg=1.000000e+00\n",
      "Training Softmax 10 / 24 with learning_rate=1.000000e-03 and reg=1.000000e+01\n",
      "Training Softmax 11 / 24 with learning_rate=1.000000e-03 and reg=3.000000e+00\n",
      "Training Softmax 12 / 24 with learning_rate=1.000000e-03 and reg=5.000000e+00\n",
      "Training Softmax 13 / 24 with learning_rate=1.000000e-02 and reg=1.000000e+00\n",
      "Training Softmax 14 / 24 with learning_rate=1.000000e-02 and reg=1.000000e+01\n",
      "Training Softmax 15 / 24 with learning_rate=1.000000e-02 and reg=3.000000e+00\n",
      "Training Softmax 16 / 24 with learning_rate=1.000000e-02 and reg=5.000000e+00\n",
      "Training Softmax 17 / 24 with learning_rate=3.000000e-02 and reg=1.000000e+00\n",
      "Training Softmax 18 / 24 with learning_rate=3.000000e-02 and reg=1.000000e+01\n",
      "Training Softmax 19 / 24 with learning_rate=3.000000e-02 and reg=3.000000e+00\n",
      "Training Softmax 20 / 24 with learning_rate=3.000000e-02 and reg=5.000000e+00\n",
      "Training Softmax 21 / 24 with learning_rate=1.000000e-01 and reg=1.000000e+00\n",
      "Training Softmax 22 / 24 with learning_rate=1.000000e-01 and reg=1.000000e+01\n",
      "Training Softmax 23 / 24 with learning_rate=1.000000e-01 and reg=3.000000e+00\n",
      "Training Softmax 24 / 24 with learning_rate=1.000000e-01 and reg=5.000000e+00\n",
      "lr 1.000000e-04 reg 1.000000e+00 train accuracy: 26.400000 val accuracy: 26.390000\n",
      "lr 1.000000e-04 reg 3.000000e+00 train accuracy: 26.067500 val accuracy: 26.250000\n",
      "lr 1.000000e-04 reg 5.000000e+00 train accuracy: 25.735000 val accuracy: 25.940000\n",
      "lr 1.000000e-04 reg 1.000000e+01 train accuracy: 25.325000 val accuracy: 25.370000\n",
      "lr 1.000000e-03 reg 1.000000e+00 train accuracy: 29.605000 val accuracy: 29.620000\n",
      "lr 1.000000e-03 reg 3.000000e+00 train accuracy: 26.805000 val accuracy: 26.800000\n",
      "lr 1.000000e-03 reg 5.000000e+00 train accuracy: 25.857500 val accuracy: 25.800000\n",
      "lr 1.000000e-03 reg 1.000000e+01 train accuracy: 24.980000 val accuracy: 25.070000\n",
      "lr 3.000000e-03 reg 1.000000e+00 train accuracy: 29.400000 val accuracy: 29.310000\n",
      "lr 3.000000e-03 reg 3.000000e+00 train accuracy: 26.570000 val accuracy: 26.420000\n",
      "lr 3.000000e-03 reg 5.000000e+00 train accuracy: 25.670000 val accuracy: 25.720000\n",
      "lr 3.000000e-03 reg 1.000000e+01 train accuracy: 24.950000 val accuracy: 24.990000\n",
      "lr 1.000000e-02 reg 1.000000e+00 train accuracy: 29.352500 val accuracy: 29.150000\n",
      "lr 1.000000e-02 reg 3.000000e+00 train accuracy: 26.402500 val accuracy: 26.480000\n",
      "lr 1.000000e-02 reg 5.000000e+00 train accuracy: 25.672500 val accuracy: 25.370000\n",
      "lr 1.000000e-02 reg 1.000000e+01 train accuracy: 24.945000 val accuracy: 24.720000\n",
      "lr 3.000000e-02 reg 1.000000e+00 train accuracy: 29.127500 val accuracy: 28.990000\n",
      "lr 3.000000e-02 reg 3.000000e+00 train accuracy: 26.422500 val accuracy: 26.230000\n",
      "lr 3.000000e-02 reg 5.000000e+00 train accuracy: 25.730000 val accuracy: 25.610000\n",
      "lr 3.000000e-02 reg 1.000000e+01 train accuracy: 25.165000 val accuracy: 25.220000\n",
      "lr 1.000000e-01 reg 1.000000e+00 train accuracy: 29.042500 val accuracy: 28.860000\n",
      "lr 1.000000e-01 reg 3.000000e+00 train accuracy: 25.565000 val accuracy: 25.060000\n",
      "lr 1.000000e-01 reg 5.000000e+00 train accuracy: 21.192500 val accuracy: 20.860000\n",
      "lr 1.000000e-01 reg 1.000000e+01 train accuracy: 5.240000 val accuracy: 5.190000\n",
      "best validation accuracy achieved during cross-validation: 29.620000\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import eecs598\n",
    "from linear_classifier import Softmax, softmax_get_search_params, test_one_param_set\n",
    "\n",
    "# YOUR_TURN: find the best learning_rates and regularization_strengths combination\n",
    "#            in 'softmax_get_search_params'\n",
    "learning_rates, regularization_strengths = softmax_get_search_params()\n",
    "num_models = len(learning_rates) * len(regularization_strengths)\n",
    "\n",
    "####\n",
    "# It is okay to comment out the following conditions when you are working on svm_get_search_params.\n",
    "# But, please do not forget to reset back to the original setting once you are done.\n",
    "if num_models > 25:\n",
    "  raise Exception(\"Please do not test/submit more than 25 items at once\")\n",
    "elif num_models < 5:\n",
    "  raise Exception(\"Please present at least 5 parameter sets in your final ipynb\")\n",
    "####\n",
    "\n",
    "\n",
    "i = 0\n",
    "# As before, store your cross-validation results in this dictionary.\n",
    "# The keys should be tuples of (learning_rate, regularization_strength) and\n",
    "# the values should be tuples (train_acc, val_acc)\n",
    "results = {}\n",
    "best_val = -1.0   # The highest validation accuracy that we have seen so far.\n",
    "best_softmax_model = None # The Softmax object that achieved the highest validation rate.\n",
    "num_iters = 2000 # number of iterations\n",
    "\n",
    "for lr in learning_rates:\n",
    "  for reg in regularization_strengths:\n",
    "    i += 1\n",
    "    print('Training Softmax %d / %d with learning_rate=%e and reg=%e'\n",
    "          % (i, num_models, lr, reg))\n",
    "    \n",
    "    eecs598.reset_seed(0)\n",
    "    cand_softmax_model, cand_train_acc, cand_val_acc = test_one_param_set(Softmax(), data_dict, lr, reg, num_iters)\n",
    "\n",
    "    if cand_val_acc > best_val:\n",
    "      best_val = cand_val_acc\n",
    "      best_softmax_model = cand_softmax_model # save the classifier\n",
    "    results[(lr, reg)] = (cand_train_acc, cand_val_acc)\n",
    "\n",
    "\n",
    "# Print out results.\n",
    "for lr, reg in sorted(results):\n",
    "  train_acc, val_acc = results[(lr, reg)]\n",
    "  print('lr %e reg %e train accuracy: %f val accuracy: %f' % (\n",
    "         lr, reg, train_acc, val_acc))\n",
    "    \n",
    "print('best validation accuracy achieved during cross-validation: %f' % best_val)\n",
    "\n",
    "# save the best model\n",
    "# path = os.path.join(GOOGLE_DRIVE_PATH, 'softmax_best_model.pt')\n",
    "# best_softmax_model.save(path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "efougAmNCFLo"
   },
   "source": [
    "Run the following to visualize your cross-validation results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 713
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 102558,
     "status": "ok",
     "timestamp": 1600042654440,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "IVhRe3-DBjPr",
    "outputId": "174e7c86-c8e7-444e-9fc0-2ba5ebeaac05"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_scatter = [math.log10(x[0]) for x in results]\n",
    "y_scatter = [math.log10(x[1]) for x in results]\n",
    "\n",
    "# plot training accuracy\n",
    "marker_size = 100\n",
    "colors = [results[x][0] for x in results]\n",
    "plt.scatter(x_scatter, y_scatter, marker_size, c=colors, cmap='viridis')\n",
    "plt.colorbar()\n",
    "plt.xlabel('log learning rate')\n",
    "plt.ylabel('log regularization strength')\n",
    "plt.title('CIFAR-10 training accuracy')\n",
    "plt.gcf().set_size_inches(8, 5)\n",
    "plt.show()\n",
    "\n",
    "# plot validation accuracy\n",
    "colors = [results[x][1] for x in results] # default size of markers is 20\n",
    "plt.scatter(x_scatter, y_scatter, marker_size, c=colors, cmap='viridis')\n",
    "plt.colorbar()\n",
    "plt.xlabel('log learning rate')\n",
    "plt.ylabel('log regularization strength')\n",
    "plt.title('CIFAR-10 validation accuracy')\n",
    "plt.gcf().set_size_inches(8, 5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "fbOlUcv6J7MM"
   },
   "source": [
    "Them, evaluate the performance of your best model on test set. To get full credit for this assignment you should achieve a test-set accuracy above 0.36.\n",
    "\n",
    "(Our best was just around 39.9% -- did you beat us?)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 101868,
     "status": "ok",
     "timestamp": 1600042654843,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "-wxkVdB-1ddx",
    "outputId": "f5ec9727-12f1-4efc-e333-e373b8a79f93"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "softmax on raw pixels final test set accuracy: 0.299300\n"
     ]
    }
   ],
   "source": [
    "y_test_pred = best_softmax_model.predict(data_dict['X_test'])\n",
    "test_accuracy = torch.mean((data_dict['y_test'] == y_test_pred).double())\n",
    "print('softmax on raw pixels final test set accuracy: %f' % (test_accuracy, ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Joo4RbeoKECC"
   },
   "source": [
    "Finally, let's visualize the learned weights for each class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 385
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 100881,
     "status": "ok",
     "timestamp": 1600042655002,
     "user": {
      "displayName": "Yunseok Jang",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gji2utsrQJWXntm3ishdCA23wmdDA4QyRS8UrqQsEQ=s64",
      "userId": "10051210866960976186"
     },
     "user_tz": 240
    },
    "id": "XDfxI7mR1ddz",
    "outputId": "30116f98-b621-4c29-b7b7-710f8d1626bb"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x576 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "w = best_softmax_model.W[:-1,:] # strip out the bias\n",
    "w = w.reshape(3, 32, 32, 10)\n",
    "w = w.transpose(0, 2).transpose(1, 0)\n",
    "\n",
    "w_min, w_max = torch.min(w), torch.max(w)\n",
    "\n",
    "classes = ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "for i in range(10):\n",
    "  plt.subplot(2, 5, i + 1)\n",
    "\n",
    "  # Rescale the weights to be between 0 and 255\n",
    "  wimg = 255.0 * (w[:, :, :, i].squeeze() - w_min) / (w_max - w_min)\n",
    "  plt.imshow(wimg.type(torch.uint8).cpu())\n",
    "  plt.axis('off')\n",
    "  plt.title(classes[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "GsmqO2p2XYhi"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "collapsed_sections": [
    "FrfeHl_-m4V-",
    "Q7ymI0aZ2W1b",
    "ynKS05gJ4iBo",
    "fN1SShPR4lJV",
    "-Yv3zQYw5B3s",
    "0Lvdm4fm7iJC",
    "DkuwyMY27RxS"
   ],
   "name": "linear_classifier.ipynb",
   "provenance": [],
   "toc_visible": true
  },
  "kernelspec": {
   "display_name": "Python 3.8.12 ('myenv')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  },
  "vscode": {
   "interpreter": {
    "hash": "de1e89af3ef8b17e93d79e53c27fdd6267335e03ee420ef3296d6319bf4dd9be"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
